Semantic networks are an old and well-known data representation method. A recent overview of the field and a detailed description of a particular semantic network can be found in H. Helbig: Knowledge Representation and the Semantics of Natural Language, Springer, 2006, which is hereby incorporated herein in its entirety.
A semantic network comprises nodes, typically representing classes and individuals, and links between nodes (or built-in values such as numbers or strings). Links may be unary, binary, ternary, or of other arities. In some semantic networks links may also refer to other links.
Known semantic network based knowledge representation systems have been relatively small scale, with up to some millions or tens of millions of nodes or links. However, for a large scale knowledge processing system, the semantic network may need to scale to billions of nodes, most of which describe individual objects and individual events.
Current semantic networks do not scale well to such sizes. The present invention aims to improve the scalability of semantic network based knowledge representation systems and to improve their performance.